期刊文献+

基于图像分块和改进Criminisi算法的图像修复方法 被引量:6

Image inpainting method based on image partition and improved Criminisi algorithm
在线阅读 下载PDF
导出
摘要 图像在采集和传输过程中,由于多种因素的干扰,图像会受到一定的损伤,导致图像质量下降。针对目前图像修复方法存在修复时间长,修复效果有限等不足,提出基于图像分块和改进Criminisi算法的图像修复方法。首先将原始图像划分为多个子块,然后采用Criminisi算法对每一子块图像进行修复,并针对传统Criminisi算法存在的局限性进行相应的改进,最后通过具体的图像修复实验分析所提方法的有效性和优越性。结果表明,所提方法减少了图像修复时间,可以加快图像修复的速度,图像修复后的质量要远优于对比方法,是一种速度快、效果好的图像修复方法。 In the process of image acquisition and transmission,the image may be damaged to a certain extent due to the interference of many factors,resulting in the degradation of image quality.There are some shortcomings in the current image inpainting methods,such as long inpaiting time and limited repair effect.Therefore,an image inpainting method based on image segmentation and improved Criminisi algorithm is proposed.In the method,the original image is divided into several sub⁃blocks,and then each image sub⁃block is renovated with the Criminisi algorithm.The corresponding timing is changed for the limitations of the traditional Criminisi algorithm.Finauy,the effectiveness and superiority of the proposed method are analyzed by specific image inpainting experiments.The results show that the proposed method can shorten the duration of image restoration,accelerate the speed of image restoration,and the quality of image restoration is much better than that of contrast method.It is a fast and effective image restoration method.
作者 齐巨慧 QI Juhui(Taiyuan University of Technology,Taiyuan 030024,China)
机构地区 太原理工大学
出处 《现代电子技术》 北大核心 2020年第1期63-66,共4页 Modern Electronics Technique
关键词 图像修复 图像子块 Criminisi算法 修复效率 修复效果 实验分析 image inpainting image sub⁃block Criminisi algorithm restoration efficiency restoration effect experimen⁃tal analysis
  • 相关文献

参考文献14

二级参考文献117

  • 1屈磊,韦穗,梁栋,王年.快速自适应模板图像修复算法[J].中国图象图形学报,2008,13(1):24-28. 被引量:13
  • 2朱晓临,陈晓冬,朱园珠,陈嫚,李雪艳.基于显著结构重构与纹理合成的图像修复算法[J].图学学报,2014,35(3):336-342. 被引量:12
  • 3李鸿林,张忠民,羿宗琪.中值滤波技术在图像处理中的应用[J].信息技术,2004,28(7):26-27. 被引量:29
  • 4Drori I, Cohen-Or D, Yeshurun H. Fragment-based image completion[ C ]//Proceedings of ACM SIGGRAPH. New York, USA: ACM, 2003 : 303-312.
  • 5Criminisi A, Perez P, Toyama K. Object removal by exemplar- based inpainting [ C ]//Proceedings of 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Madison: Wisconsin, 2003:721-728.
  • 6Andrei R, Marcel J T, Jan B. Edge-based image restoration [ J]. IEEE Transactions on Image Processing, 2005, 14 (10) : 1454-1468.
  • 7Sun J, Yuan L, Jia J Y, et al. Image completion with structure propagation [ C ]//Proceedings of ACM SIGGRAPH. New York, USA: ACM, 2035, 24 (3) : 861-868.
  • 8Shen M F, Li B. Structure and texture image iupainting based on region segmentation [ C ]// Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing. Hawaii, USA : Honolulu, 2007: 701 -704.
  • 9Wang M Q, Han G Q, Tu Y Q. Edge-based image completing guided by region segmentation [ C ]// Proceedings of ISECS International Colloquium Computing, Communication,Control, and Management. Guangzhou, China: IEEE, 2008 : 152-156.
  • 10Wong A, Orchard J. A nonlocal-means approach to exemplar- based inpainting [ C ]// Proceedings of 2008 the 15th IEEE International Conference on Image Processing. San Diego, CA, USA: IEEE, 2008: 2600-2603.

共引文献121

同被引文献44

引证文献6

二级引证文献13

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部